Information retrieving system, information retrieving method, and information retrieving program

ABSTRACT

In this invention, a database in which a keyword and an attribute of the keyword are stored together with a document ID for discriminating a source document is arranged, at least one keyword and/or retrieval key constituted by attribute information which is not specified as a keyword is input, and the database is retrieved on the basis of the keyword and/or the attribute of the attribute information. As a result, the source document can be specified by the keyword input as the retrieval key, and retrieval intention is reflected by the attribute information input as the retrieval key.

CROSS REFERENCE TO RELATED APPLICATIONS

The disclosure of Japanese Patent Application No.JP2003-190556, filedJul. 2, 2003, entitled “Information Retrieving System, InformationRetrieving Method, and Information Retrieving Program.” The contents ofthat application are incorporated herein by reference in their entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates an information retrieving system, aninformation retrieving method, and an information retrieving programwhich can be applied to, for example, retrieval of an electronicdocument or a word in an electronic document with an arbitrary keyword.

2. Description of the Related Art

A retrieval engine disclosed in the Internet is established as a toolthat lists addresses (URLs) of Web pages related to input keywords onthe basis of a predetermined order of priority to make it possible tochecks any and all things from business articles to objects forpleasure.

However, when a matter (for example, a place or the like) related to aretrieval keyword is desired to be known, a large number of documents inwhich the matter is not described are listed in a retrieval result inretrieval using only a keyword. Even though the documents include thematter, the documents must be read, and it is difficult to efficientlyknow the matter.

As a method of solve this problem, a method disclosed in Japanese PatentLaid-open Publication No. 2002-132811 is known. In this method, aquestion sentence (for example, “What is the capital of Japan?”) isinput, after the question sentence is analyzed, a related document isretrieved according to the analysis result. In addition, an answer tothe question sentence (for example, “Tokyo”) is obtained and output.

However, in a method described in Japanese Patent Laid-open PublicationNo. 2002-132811, since an answer is formed on the basis of a documentserving as a retrieval result of a keyword to a document database, theretrieval result frequently includes a sentence in which a word servingas an answer is not described, and retrieval efficiency is deteriorated.Furthermore, since the answer is formed by searching the document, longprocessing time and high processing cost are required when the answer isformed.

SUMMARY OF THE INVENTION

The present invention provides an information retrieving apparatus, aninformation retrieving method, and an information retrieving programwhich can rapidly and efficiently obtain an appropriate retrieval resultwhen a retrieval intention is a matter related to a keyword.

In order to solve the above problem, an information retrieving systemaccording to the first aspect of the present invention includes: (1) adatabase in which a keyword and an attribute of the keyword are storedtogether with a document ID for discriminating a source document of thekeyword; (2) a retrieval key input section which captures at least onekeyword and/or retrieval key constituted by attribute information whichis not specified as a keyword; (3) a retrieval section which retrievesinformation from the database on the basis of the keyword and/or theattribute of the attribute information captured by the retrieval keyinput section; and (4) an output section which outputs an obtainedretrieval result.

An information retrieving method according to the second aspect of thepresent invention includes: (0) a step of using a database in which akeyword and an attribute of the keyword are stored together with adocument ID for discriminating a source document of the keyword; (1) aretrieval key input step of capturing at least one keyword and/orretrieval key constituted by attribute information which is notspecified as a keyword; (2) a retrieval step of retrieving informationfrom the database on the basis of the keyword and/or the attribute ofthe attribute information captured in the retrieval key input step; and(3) an output step of outputting an obtained retrieval result.

An information retrieving program according to the third aspect of thepresent invention is obtained by causing a computer to execute theinformation retrieving method according to the second aspect of thepresent invention. The steps of the information retrieving methodaccording to the second aspect of the present invention are described bycodes which can be executed by the computer. The data of the databaseused in the information retrieving method according to the second aspectof the present invention is also described by codes which can beaccessed by the computer.

As described above, according to the present invention, an informationretrieving system, an information retrieving method, and an informationretrieving program that can rapidly and efficiently obtain anappropriate retrieval result when a thing which is desired to beretrieved is related to a keyword can be realized.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing a functional configuration of aninformation retrieving system according to the embodiment;

FIG. 2 is a sequence diagram showing a data registration operationaccording to the embodiment;

FIG. 3 is a diagram for explaining an example of an input documentaccording to the embodiment;

FIG. 4 is a diagram for explaining a morphological analysis result andan attribute analysis result according to the embodiment;

FIG. 5 is a diagram for explaining registration of a keyword or the likein a database according to the embodiment;

FIG. 6 is a sequence diagram showing a data retrieving operationaccording to the embodiment;

FIG. 7 is a diagram for explaining an example of a retrieval keyaccording to the embodiment;

FIG. 8 is a diagram for explaining a data configuration of a retrievalrule recording unit according to the embodiment; and

FIG. 9 is a diagram for explaining an attribute conversion result of anattribute keyword according to the embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

(A) Embodiment

An embodiment of an information retrieving system, an informationretrieving method, and an information retrieving program according tothe present invention will be described below with reference to theaccompanying drawings.

(A-1) Configuration of Embodiment

FIG. 1 is a block diagram showing a functional configuration of aninformation retrieving system according to the embodiment. Theinformation retrieving system according to the embodiment is constructedby installing an information retrieving program (including fixed data)in one information processing apparatus typified by a personal computeror the like or constructed by distributing processing routines of aninformation retrieving program to a plurality of information processingapparatuses such as personal computers and servers. However,functionally, the information retrieving system can have a configurationshown in FIG. 1. The embodiment will be described below as a hardwarerealized by one information processing apparatus.

An information retrieving system 1 according to the embodiment isroughly constituted by a data registration section 10, a database 20,and a data retrieving section 30.

The data registration section 10 stores data or the like of a documentwhich can serve as a retrieval target in the database 20. The dataregistration section 10 has a document input section 11, a keywordextraction section 12, a morphological analysis section 13, and anattribute analysis section 14.

The document input section 11 is to input a document (for example, anelectronic document) registered in the database 20. For example, thedocument input section 11 corresponds to, in addition to a keyboard, anaccess device for a recording medium such as a flexible disk or aCD-ROM, a combination of an image scanner and an OCR (Optical CharacterReader), an external data receiving configuration, or the like.

The keyword extraction section 12 extracts a keyword or the like fromthe input document inputted by the document input section 11 by usingthe morphological analysis section 13 and the attribute analysis section14. For example, the keyword extraction section 12 corresponds to a CPUand a program (including fixed data) section executed by the CPU.

The morphological analysis section 13 divides the input document intomorphemes and gives word-class information to the morphemes.

For example, the morphological analysis section 13 corresponds to a CPUor a program (including fixed data) section executed by the CPU.

The morphological analysis section 13 is used by the keyword extractionsection 12 in keyword extraction. The morphological analysis section 13may have not only a morphological analysis function but also a parsingfunction.

The attribute analysis section 14 analyses an attribute to amorphological analysis result obtained by the morphological analysissection 13. For example, the attribute analysis section 14 correspondsto a CPU and a program (including fixed data) executed by the CPU.

The attribute analysis section 14 is used by the keyword extractionsection 12 in keyword extraction. In this case, the attribute may beinformation except for a word class. For example, a meaning or the likeheld by the word (keyword) can be applied.

The database 20 stores document data or the like which can serve as aretrieval target. For example, the database 20 is realized by alarge-capacity storage device such as a hard disk device or an opticaldisk device. In the database 20, at least one combination of data of anelectronic document, a keyword and an attributes related to the data,and data constituted by an attribute value is stored.

The data retrieving section 30 retrieves a corresponding electronicdocument or sentence from the database 20 depending on a user input suchas a keyword. The data retrieving section 30 has a retrieval key inputsection 31, a retrieving section main body 32, a retrieval key analysissection 33, an attribute rule storage section 34, and an output section35.

The retrieval key input section 31 inputs a retrieval key constituted byat least one keyword. Combination conditions (AND, OR, and the like)between keywords may be able to be input as retrieval information. Theretrieval key input section 31, for example, corresponds to a keyboard,a mouse, and the like which are related to a display screen to make itpossible to input data. The retrieval key input section 31 alsocorresponds to an access configuration or the like for a recordingmedium which can be input as a retrieving file.

The retrieving section main body 32 analyzes a retrieval key andretrieves a corresponding document from the database 20. For example,the retrieving section main body 32 corresponds to a CPU and a program(including fixed data) section executed by the CPU.

The retrieval key analysis section 33 obtains information of anattribute based on an attribute rule stored in the attribute rulestorage section 34 with respect to a keyword constituting a retrievalkey. For example, the retrieval key analysis section 33 corresponds to aCPU and a program (including fixed data) executed by the CPU. Theretrieval key analysis section 33 is executed under the control of theretrieving section main body 32.

The attribute rule storage section 34 stores a corresponding informationbetween a keyword and an attribute. For example, the attribute rulestorage section 34 is realized to have a table configuration in anonvolatile memory such as an EEPROM. The storage contents of theattribute rule storage section 34 correspond to attribute analyzinginformation stored in the attribute analysis section 14 described above.For example, the same attribute can be obtained for the same term (forexample, a morpheme or a keyword).

The output section 35 outputs a retrieval result (for example, adocument) for a retrieval key from the database 20. The output section35 corresponds to not only a display or a printer but also a storagedevice or a communication section for file information depending onconditions.

(A-2) Operation of Embodiment

An operation of the information retrieving system (informationretrieving method) constituted by the above sections will be describedbelow with reference to the drawings.

(A-2-1) Registration Operation for Database

An operation of causing the data registration section 10 to registerdata in the database 20 will be described below with reference to FIG.2.

The document input section 11 captures an electronic document to beregistered in the database 20 (S1). The document, i.e., may be capturedby inputting an existing document, or may be loaded from a Web page byautomatically circulating on the Internet. In the latter case, anunnecessary tag, an unnecessary image, an unnecessary advertisement, orthe like is preferably removed from the document.

FIG. 3 shows captured electronic documents. Document IDs fordiscriminating the documents from each other are given to the documents,respectively. The document IDs are given by the database 20. When aregion for document IDs is secured in design of the database 20 toautomatically set the document IDs, the document IDs are added as 1, 2,3, . . . , or can employ unique values when the documents are registeredin the database 20.

The keyword extraction section 12 stores the electronic documentsobtained by the document input section 11 in the database 20 andextracts a keyword (S2).

The keyword extraction process includes a process (S3) of separatingwords (morphemes) constituting a sentence and obtaining word classes ofthe words by a morphological analysis section 13 and a process (S4) ofgiving the attributes of the words (attributes except for the wordclasses of the words) and attribute values by the attribute analysissection 14 to form a keyword. The keyword extraction section 12registers the formed keyword and the attribute (attribute name and theattribute value) in the database 20 (S5).

The attribute name, for example, can be obtained by referring to a table(e.g., “Japan: nation name”, “president: slot”, and the like) whichcauses words to respond to attribute names, or can be obtained from aword dictionary with attributes. In attribute analysis, in addition, agiving rule for an unknown word is applied. In the attribute analysissection 14, an attribute may be given to a plurality of words separatedfrom each other in a morphological analysis result. As an existingmorphological analysis section, a morphological analysis section whichcan analyze an attribute is present. However, such a morphologicalanalysis section 13 is applied, the attribute analysis section 14 can beomitted.

FIG. 4 shows a morphological analysis result and an attribute analysisresult according to a document (first sentence) having a document ID of“2” in FIG. 3.

In the example in FIG. 4, attributes “full name” and “organization” aregiven to an unknown word “BB”. This is based on a prepared giving rulethat gives attributes “full name” and “organization” to an unknown wordimmediately following a word “president”.

If an input sentence is “president of electronic company A is BB”,parsing may be also performed to capture that the unknown word “BB” is afull name. The number of attributes to be given may be 2 or more, andsome word may not have an attribute. In addition, an attribute is givento the whole of a word string such as “president of electric company A”to obtain a keyword, or attributes may be separately given to the words“electric company A” and “president” (see FIG. 5) which are obtained bydividing the word string to obtain keywords. For example, attributes arepreferably given to the whole of a word string having numerals such as“eighteen years old”, “ten billion yen”, “one hundred million persons”.

A keyword, for example, is limited to a word class such as a noun.

An existing keyword extraction method (forming method) related to adocument can be applied except that an attribute is given.

FIG. 5 shows a data configuration of a keyword stored in the database 20by keyword extraction.

One record is constituted by a document ID of an extraction source ofthe keyword, the keyword (character string), an attribute (attributename), and an attribute value. The attribute value mentioned here is,for example, a position where the keyword appears in the sentence (theposition of a first character of the keyword in the sentence). When anattribute is set as an item of a keyword record, a narrow-down processusing an attribute name in document retrieval can be performed. Theattribute and the attribute value are not always necessary, and may bethe value “null”.

(A-2-2) Retrieving Operation from Database

A document retrieving operation from the database 20 by the dataretrieving section 30 will be described below with reference to FIG. 6.

The retrieval key input section 31 captures at least one keyword (S11).The keyword may be captured by inputting a keyword by a user, or may beloaded from another execution module.

FIG. 7 shows retrieval keywords. In FIG. 7, retrieval of an electronicdocument including three keywords “who”, “president”, and “electriccompany A” is required. In this case, a blank between keywords means“AND”. Unlike FIG. 7, a format that can clearly indicate “AND” or “OR”may be used. In addition to FIG. 7, the maximum number of documentsoutput by retrieval may be designated.

In FIG. 7, an interrogative word “who” does not mean retrieval of adocument including “who” itself. The interrogative word means retrievalof a document including a keyword having the same attribute as theattribute held by “who” (such a keyword is called an attribute keywordin the following description). In other words, “who” does not mean akeyword, and rather defines an attribute. In this embodiment, inaddition to “who”, various attribute keywords such as “when”, “where”,“how old”, and “how many persons” can be applied. The attribute keyworddepends on the storage contents of the attribute rule storage section34.

FIG. 7 shows a retrieval keyword input when a user tries to know whether“Who is the president of electric company A?” from a retrieval document.Such retrieval is performed when a user wants to know the contents of anentire document such as a news article and to know only a predeterminedmatter through the retrieval document.

When a user wants to perform retrieval by using a character “who” itselfas a keyword, an escape process such as “[who]” is performed (using anescape code []).

The retrieving section main body 32 plays a central role (under thecontrol of the retrieving section main body 32), by using an inputkeyword, a corresponding document is retrieved from the database 20(S12). The retrieving section main body 32 may not execute retrievalwhen all retrieval keywords or retrieval keyword groups are attributekeywords or when the number of keywords except for attribute keywords isa predetermined number or less, and may output that the retrievalkeywords and the retrieval keyword groups are attribute keywords or thatthe number of keywords except for attribute keywords is thepredetermined number or less.

The retrieving section main body 32 calls the retrieval key analysissection 33 to cause the retrieval key analysis section 33 to executeanalysis of an attribute to the input keyword (S13). At this time, theretrieval key analysis section 33 uses the storage contents of theattribute rule storage section 34 to given an attribute to the keyword(S13′).

FIG. 8 shows an example obtained when the attribute rule storage section34 is constituted by a corresponding table. In FIG. 8, conversion rulessuch as “who” to “full name”, “when” to “date and time, season”, “where”to “address, organization, place name, nation name” are held. When notonly these interrogative words but also conversion rules for keywordsare increased in number, the retrieving section main body 32 can copewith various attributes. For example, numerical attributes such as “howold” and “how many persons” may be thinkable. In addition, an attributekeyword such as “full name” which is not an interrogative word ispreferably prepared. In this manner, the attribute keyword name and theattribute name can also be made equal to each other. Attribute analysisof a retrieval key by the retrieval key analysis section 33 is the sameanalysis as that performed by the attribute analysis section 14. If akeyword except for an attribute keyword is used, the same attribute isgiven to the same word. An attribute may be given to a normal keywordexcept for an attribute keyword.

FIG. 9 shows an attribute analysis result obtained after the processperformed by the retrieval key analysis section 33 to the inputretrieval keyword shown in FIG. 7 is finished. Attributes “full name”,“slot”, and, “organization” are given to retrieval keywords “who”,“president”, and, “electric company A” respectively. The attribute rulestorage section 34 may be designed to make it possible to give anattribute to only an attribute keyword. The attribute rule storagesection 34 may give a flag for discriminating an attribute keyword fromanother keyword.

For example, when an attribute is also given to a normal keyword, if adocument cannot be retrieved by the keyword name, the retrieval can beexecuted again such that the keyword is replaced with an attribute name.

The retrieving section main body 32 determines a keyword or an attributeused in retrieval on the basis of the attribute analysis result, and thecorresponding document is retrieved from the database 20 (S14).

In this case, with respect to the attribute keyword, a document havingthe attribute is retrieved. With respect to another keyword, retrievalmay be performed by only a keyword name or may be performed by acombination of a keyword name and an attribute name.

For example, in the attribute analysis result in FIG. 9, a documenthaving the keywords “president” and “electronic company A” and theattribute “full name” is retrieved from the database 20. In this case,as a concrete retrieving method, the following retrieving method isknown. That is, a set of corresponding document IDs is obtained byretrieval performed by only the keywords, and a set of correspondingdocument IDs is obtained by only an attribute, so that a document commonin both the sets of document IDs is obtained. In addition, a retrievingmethod that checks whether the document includes the keywords and theattribute or not is also known. The later method is preferable becausethe method has high retrieving efficiency.

When retrieval is performed by keywords “president” and “electriccompany A” and an attribute “full name”, according to the data in FIG.5, documents having document IDs “2” and “4” are retrieved. Unlike theembodiment, when “who” is not designated, documents having document IDs“1”, “2”, and “4” are retrieved in retrieval performed by inputting thekeywords “president” and “electric company A”.

When an attribute keyword is not included as a retrieval key, retrievalusing a keyword (normal keyword) is executed as a matter of course.

The retrieving section main body 32 causes the output section 35 tooutput the obtained retrieval result (S15). As an output of theretrieval result, a document ID or a document itself the keyword andattribute of which are hit may be used. When a document includes anattribute keyword as a retrieval keyword, in place of the document IDand the document itself, or in addition to the document ID and thedocument itself, a keyword serving as a designated attribute keyword maybe used.

As a retrieval result having a plurality of documents, the documents maybe output by ordering the documents by using attribute values. Forexample, when two documents having document IDs “2” and “4” areretrieved as a retrieval result, distances between character stringscalculated by attribute values of the keywords “electric company A” and“president” and the attribute “full name” are ” 10,0” in a documenthaving a document ID of “2” and “11,0” in a document having a documentID of “4”, as described by a calculation expression (will be describedlater). The priorities of the document having a short distance and thedocument ID of “2” and an answer “BB” having the attribute “full name”in the document can be increased to make an answer.

As a distance between the “electric company A” and the “full name” inthe document having the document ID of “2”, an attribute value (1) ofthe “electric company A” having a smaller attribute value (appearing atthe former place) is subtracted from an attribute value (27) of the“full name (BB)” having a larger attribute value (appearing at the laterplace) to calculate a distance between the start characters, and thenumber of characters (16) of the “electric company A” having a smallerattribute value is subtracted from the distance to calculate a distance(=27−1−16=10) between character positions of the final character of aword appearing at the former place and the first character of a wordappearing at the later place in the document. The distance between the“president” and the “full name” in the document having the document IDof “2” is given by 27−18−9=0 according to the same method of thinking asdescribed above.

On the other hand, the distance between the “electric company A” and the“full name” in the document having the document ID of “4” is given by41−28−2=11, and the distance between the “president” and the “full name”is given by 28−19−9=0.

When a plurality of distances are obtained, for example, ordering isperformed on the basis of a sum of the distances or the maximumdistance.

Such ordering may be performed to determine an output order.

When the maximum value of the number of output documents is regulated bya user, the ordering may be used to extract the number of documents upto up to the maximum number.

The retrieval result may be output on a display screen for, e.g., auser. the retrieval result may be a return value to another calledmodule (S16).

(A-3) Effect of the Embodiment

According to the above embodiment, a keyword responding to a document isstored in a database for storing the document such that attribute isgiven to the keyword, and an input of an attribute keyword may bepermitted as an input of a retrieval keyword. An attribute name of theresponding attribute keyword is obtained. The retrieve data is retrievedin the database by using the attribute name. For this reason, as aretrieval result, only a document having an attribute keyword includinga matter desired to be known can be obtained. Furthermore, a retrievalresult can be rapidly obtained while suppressing the processing cost.

In the conventional method described in Japanese Patent Laid-openPublication No. 2002-132811, an input questioned sentence is analyzed todetermine a word for retrieval, and a document including the word forretrieval is captured. Thereafter, the captured document is analyzed toobtain an answer to the questioned sentence. For this reason, a processof obtaining the answer cannot be performed at a high speed. However, inthe embodiment, the answer result can be rapidly obtained.

According to the embodiment, when “electric company A president who age”is input as a retrieval keyword, an answer to “who” and an answer to“age” can be obtained by one retrieval command. However, in theconventional method described in Japanese Patent Laid-open PublicationNo. 2002-132811, different questioned sentences are formed, and questionmust be performed twice. Therefore, process efficiency is poor.

Furthermore, according to the embodiment, in retrieval, normal keywordsand attribute keywords can be listed without being discriminated fromeach other. For this reason, for a narrow-down operation or a change ofquestions, a retrieval keyword can be easily re-input after keywords arechanged or increased in number.

Still furthermore, according to the embodiment, a preparative processfor retrieval in a data retrieving section is a process of replacing anattribute keyword with an attribute, and does not require a process ofanalyzing a sentence (questioned sentence). For this reason, the dataretrieving section employs a simple configuration (in particular, aprogram configuration).

(B) Another Embodiment

In the description of the above embodiment, all the elements arearranged on the same information processing apparatus. However, the dataregistration section 10, the database 20, and the data retrievingsection 30 may be arranged on different information processingapparatuses, respectively, so that the data retrieving section 30 canaccess the database 20 through a communication network. In addition,only the retrieval key input section 31 may be arranged on aninformation processing apparatus for a user (for example, a browserfunction), so that the other elements are arranged on anotherinformation processing apparatus.

In the embodiment, document IDs are designed to be given by the database20. However, the document IDs may be designed to be given by thedocument input section 11.

In the embodiment, the attribute rule storage section 34 storesattributes (names) in respond to attribute keywords. In contrast tothis, in respond to the attribute (names), the attribute rule storagesection 34 may store all the attribute keywords having the attributes.The attribute rule storage section 34 may employ any configuration. Forexample, in respond on to the attribute “full name”, attribute keywords“who, full name, name, stage name, anyone, . . . ” may be stored.

In the embodiment, when a word serving as either an attribute keyword ora normal keyword is used as a retrieval keyword, special inputting isperformed (using escape code) when a retrieval keyword is input as anormal keyword. However, special inputting may be performed when aretrieval keyword is input as an attribute keyword.

Furthermore, it is marked that the retrieval keyword is an attribute butan attribute keyword, and the attribute name may be directly input asthe retrieve key. For example, when “‘full name’” is input, the “fullname” is recognized as an attribute name, and the system may access thedatabase 20 without accessing the attribute rule storage section 34.

For example, when “electric company A president who age” including atleast two attribute keywords are input as retrieval keywords is input, adocument which satisfies four keys, i.e., the keywords “electric companyA” and “president” and the attributes “full name (attribute of who)” and“age (attribute of age)” may be retrieved. A document which satisfiesthree keys, i.e., the keywords “electric company A” and “president” andthe attribute “full name” and a document which satisfies three keys,i.e., the keywords “electric company A” and “president” and theattribute “age” are retrieved. If a common document is present, thecommon document is preferentially output. If a common document is notpresent, switching is performed such that data responding to therespective retrieved documents are output.

In the above embodiment, a morphological analysis section having a wordclass specifying function is applied, and the word class of a keywordresponding to a document is limited. However, the word class of thekeyword responding to the document is not limited, a morphologicalanalysis section which simply divides a document into morphemes may beapplied. In this manner, the speed of a data registration process can bemade high.

Classification of attributes is not limited to the classificationperformed in the embodiment. For example, in place of the attribute“organization”, an attribute “company” may be given to the “electriccompany A”. An attribute “unknown word” is given to an unknown word, aninput “unknown” may be permitted as an attribute keyword. In this case,when the classification of attributes is fine, retrieval by retrievalkeys including only attribute keywords may be permitted.

When the present invention is applied to a question answering systemwhich makes only an answer to a question and which does not show adocument, main information of electronic documents in the database 20can be prohibited to be stored.

The present invention can be applied to not only a question answeringsystem which expected to obtain a specific answer but also, e.g., anretrieval engine on the Internet.

1. An information retrieving system comprising: a database in which akeyword and an attribute of the keyword are stored together with adocument ID for discriminating a source document; a retrieval key inputsection which captures at least one keyword and/or retrieval keyconstituted by attribute information which is not specified as akeyword; a retrieval section which retrieves information from thedatabase on the basis of the keyword and/or the attribute of theattribute information captured by the retrieval key input section; andan output section which outputs a retrieval result obtained by theretrieval section.
 2. An information retrieving system according toclaim 1, further comprising: a document input section which captures anelectronic document serving as a source of data to be registered in thedatabase; a keyword extraction section which extracts a keyword from theelectronic document captured by the document input section; an attributegiving section which gives an attribute to the keyword extracted by thekeyword extraction section; and a registration section which registers acorrespondence of the keyword extracted by the keyword extractionsection to the attribute given by the attribute giving section in thedatabase together with a document ID unique to the electronic document.3. The information retrieving system according to claim 1, wherein theattribute information to be captured by the retrieval key input sectionhas the data format as that of the keyword captured by the retrieval keyinput section, an attribute conversion section which converts theattribute information into an attribute is further arranged, and theretrieval section uses the attribute converted by the attributeconversion section in retrieval.
 4. The information retrieving systemaccording to claim 3, wherein the retrieval key input section captures acharacter string which is subjected to an escape code process as akeyword, and captures the character string itself which is not subjectedto an escape code process as attribute information, when the characterstring can serve as either a keyword or attribute information.
 5. Theinformation retrieving system according to claim 1, wherein theretrieval section includes a keyword, to which a document ID of documenthaving the same keyword as all the keywords captured by the retrievalkey input section is given in the database, and which also has the sameattribute as that of the attribute information captured by the retrievalkey input section, in a retrieval result.
 6. The information retrievingsystem according to claim 1, wherein an attribute responding to akeyword in the database have, in addition to an attribute name,appearing position information in a source document as an attributevalue, and when the retrieval result includes a plurality of keywords,the retrieval section orders the plurality of keywords included in theretrieval result on the basis of the attribute value of the keyword inthe database and the attribute value of the same keyword in the databaseas the keyword captured by the retrieval key input section.
 7. Aninformation retrieving method comprising: a step of using a database inwhich a keyword and an attribute of the keyword are stored together witha document ID for discriminating a source document; a retrieval keyinput step of capturing at least one keyword and/or retrieval keyconstituted by attribute information which is not specified as akeyword; a retrieval step of retrieving information from the database onthe basis of the keyword and/or the attribute of the attributeinformation captured in the retrieval key input step; and an output stepof outputting a retrieval result obtained in the retrieval step.
 8. Theinformation retrieving method according to claim 7, further comprising:a document input step of capturing an electronic document serving as asource of data to be registered in the database; a keyword extractionstep of extracting a keyword from the electronic document captured inthe document input step; an attribute giving step of giving an attributeto the keyword extracted in the keyword extraction step; and aregistration step of registering a correspondence of the keywordextracted in the keyword extraction step to the attribute given in theattribute giving step in the database together with a document ID uniqueto the electronic document.
 9. The information retrieving methodaccording to claim 7, wherein the attribute information to be capturedin the retrieval key input step has the data format as that of thekeyword captured in the retrieval key input step, an attributeconversion step of converting the attribute information into anattribute is further established, and the retrieval step uses theattribute converted in the attribute conversion step in retrieval. 10.The information retrieving method according to claim 9, wherein theretrieval key input step captures a character string which is subjectedto an escape code process as a keyword, and captures the characterstring itself which is not subjected to an escape code process asattribute information, when the character string can serve as either akeyword or attribute information.
 11. The information retrieving methodaccording to claim 7, wherein the retrieval step includes a keyword, towhich a document ID of document having the same keyword as all thekeywords captured in the retrieval key input step is given in thedatabase, and which also has the same attribute as that of the attributeinformation captured by the retrieval key input section, in a retrievalresult.
 12. The information retrieving method according to claim 7,wherein an attribute responding to a keyword in the database have, inaddition to an attribute name, appearing position information in asource document as an attribute value, and when the retrieval resultincludes a plurality of keywords, the retrieval step orders theplurality of keywords included in the retrieval result on the basis ofthe attribute value of the keyword in the database and the attributevalue of the same keyword in the database as the keyword captured in theretrieval key input step.
 13. An information retrieving program whereina computer executes an information retrieving method including: a stepof using a database in which a keyword and an attribute of the keywordare stored together with a document ID for discriminating a sourcedocument; a retrieval key input step of capturing at least one keywordand/or retrieval key constituted by attribute information which is notspecified as a keyword; a retrieval step of retrieving information fromthe database on the basis of the keyword and/or the attribute of theattribute information captured in the retrieval key input step; and anoutput step of outputting a retrieval result obtained in the retrievalstep.
 14. The information retrieving program according to claim 13,wherein the computer executes the information retrieving method furtherincluding: a document input step of capturing an electronic documentserving as a source of data to be registered in the database; a keywordextraction step of extracting a keyword from the electronic documentcaptured in the document input step; an attribute giving step of givingan attribute to the keyword extracted in the keyword extraction step;and a registration step of registering a correspondence of the keywordextracted in the keyword extraction step to the attribute given in theattribute giving step in the database together with a document ID uniqueto the electronic document.
 15. The information retrieving programaccording to claim 13, wherein the computer executes the informationretrieving method in which the attribute information to be captured inthe retrieval key input step has the data format as that of the keywordcaptured in the retrieval key input step, an attribute conversion stepof converting the attribute information into an attribute is furtherestablished, and the retrieval step uses the attribute converted in theattribute conversion step in retrieval.
 16. The information retrievingprogram according to claim 15, wherein the computer executes theinformation retrieving method in which the retrieval key input stepcaptures a character string which is subjected to an escape code processas a keyword, and captures the character string itself which is notsubjected to an escape code process as attribute information, when thecharacter string can serve as either a keyword or attribute information.17. The information retrieving program according to claim 13, whereinthe computer executes the information retrieving method according to anyone of claim 15, in which the retrieval step includes a keyword, towhich a document ID of document having the same keyword as all thekeywords captured in the retrieval key input step is given in thedatabase, and which also has the same attribute as that of the attributeinformation captured by the retrieval key input section, in a retrievalresult.
 18. The information retrieving program according to claim 13,wherein the computer executes the information retrieving method in whichan attribute responding to a keyword in the database have, in additionto an attribute name, appearing position information in a sourcedocument as an attribute value, and when the retrieval result includes aplurality of keywords, the retrieval step orders the plurality ofkeywords included in the retrieval result on the basis of the attributevalue of the keyword in the database and the attribute value of the samekeyword in the database as the keyword captured in the retrieval keyinput step.
 19. The information retrieving program according to claim13, wherein the steps are described in a code which can be executed by acomputer, and the data of the database is also described in a code whichcan be accessed by the computer.